Senior Data Engineer

About PixonalPixonal develops secure decision intelligence systems for governments and large enterprises in high-stakes environments. Our platform, Llumen, integrates data from multiple sources into a unified intelligence foundation, enabling leaders to make informed decisions in complex operational contexts. With a governed semantic layer, visual intelligence tools, and AI-native workflows, we enhance clarity and institutional trust in critical decisions. Governance-first AI and strong compliance are core to how we operate.Role DescriptionAs a Senior Data Engineer, you will design, develop, and optimize robust data solutions to support the delivery of decision intelligence systems. You will manage ETL pipelines, develop and maintain data warehouses, create efficient data models, and ensure seamless integration with APIs and other data sources. You will work across customer engagements and contribute to our in-house Llumen DataFlows engine — and will be forward-deployed with key customers to ensure smooth data integration and ongoing reliability. Collaboration with teams to analyze complex data requirements and delivery of scalable, high-performance data solutions are central to the role.ResponsibilitiesDesign and implement data pipelines — ETL workflows, ingestion from diverse sources (PostgreSQL, MySQL, MSSQL, MongoDB, REST APIs, file systems, IoT, GIS, or other technology stacks), and transformation for Llumen consumptionData warehousing and modeling — Develop and maintain data warehouses; create efficient, scalable data models and architecturesExtend and mature Llumen DataFlows — Our in-house workflow orchestration and ETL engine; visual workflow design, scheduling, monitoring, and Dev/UAT/Prod promotionSupport customer integrations — Work with customer data teams on connectivity, schemas, and interfaces; advise on staging, ETL, and data landing zonesEnsure governance and compliance — Align with data classification, residency, governance, and security requirements (SOC2, ISO 27001)Contribute to architecture — Schema design, performance tuning, observability (Prometheus, Grafana), and scalable patterns for pipeline orchestrationQualifications5+ years of data engineering experience (ETL, pipelines, data integration)Proficiency in data modeling and data warehousing; ability to create efficient, scalable data architecturesStrong Python and SQL; experience with workflow orchestration (Airflow, Prefect, or similar)Hands-on experience with PostgreSQL, REST APIs, and file-based ingestion (CSV, Excel, JSON)Data analytics skills — deriving meaningful insights from structured and unstructured dataFamiliarity with Kubernetes and cloud-based data platforms (Azure preferred)Understanding of data governance — classification, residency, security controlsProven track record working on decision-critical or large-scale data systemsProblem-solving mindset with strong communication and teamwork skillsBachelor's or Master's degree in Computer Science, Data Engineering, or a related disciplineExperience with PostGIS is a plusExposure to AI/ML pipelines or RAG-style data flows is a plusFamiliarity with UAE DDIS or similar regional data standards is a plusRelevant TechnologiesData — PostgreSQL (PostGIS), as well as any other technology stack our customers may be usingETL & Workflow — Llumen DataFlows (in-house), or any other ETL platform our customers may be usingLanguages & Frameworks — SQL, Python, REST APIsInfrastructure — Azure (PostgreSQL, Redis, Key Vault, Blob Storage)Monitoring — Prometheus, Grafana, ELK/Loki, Azure Log AnalyticsBenefitsCompetitive salary and benefitsWork on a product at the intersection of AI, analytics, and enterprise dataStrong engineering culture: PR-based workflow, code review, security-first mindsetExposure to enterprise and government customers with complex data landscapes